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Risk-sensitive Markov decision problems under model uncertainty: finite time horizon case

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 نشر من قبل Tao Chen
 تاريخ النشر 2021
  مجال البحث
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In this paper we study a class of risk-sensitive Markovian control problems in discrete time subject to model uncertainty. We consider a risk-sensitive discounted cost criterion with finite time horizon. The used methodology is the one of adaptive robust control combined with machine learning.



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